comp.heatmap {CINdex} | R Documentation

## A comprehensive heatmap function that plots Chromosome and Cytoband heatmaps

### Description

When the `run.cin.chr` and `run.cyto.chr` functions are called, we get Chromosome and Cytoband CIN values for various gain/loss threshold settings. This `comp.heatmap` function can be used to pick the best threshold for the input data. It plots heatmaps for two groups of interest (case and control) for all the input gain/loss threshold settings. By visually checking the heatmaps, the user can pick the threshold/setting that shows the best contrast between two groups of interest. Steps: #Step 1: Run cytoband CIN or chromosome CIN - using `run.cin.chr()` or `run.cin.cyto()` #Step 2: Call this function to create chromosome or cytoband level heatmaps. Pick gain/loss threshold appropriate for data. See vignette for more details.

### Usage

    comp.heatmap(R_or_C = "Regular", clinical.inf = NULL, genome.ucsc = NULL,
      in.folder.name = "output_chr_cin", out.folder.name = "output_chr_plots",
      plot.choice = "png", base.color = "black", thr.gain = c(2.5, 2.25, 2.1),
      thr.loss = c(1.5, 1.75, 1.9), V.def = 2:3, V.mode = c("sum", "amp",
      "del"))

### Arguments

`R_or_C` | The value'Regular' plots chromosome level heatmap and 'Cytobands' plots cytoband level heatmaps
`clinical.inf` | An n*2 matrix, the 1st column is 'sample name', the second is 'label'
`genome.ucsc` | A Reference genome
`in.folder.name` | Name of folder where the Chromsome CIN or Cytoband CIN objects are present
`out.folder.name` | Name of folder where the Chromosome heatmaps or Cytoband heatmaps will be saved
`plot.choice` | A choice of whether the heatmaps should be .png or .pdf format
`base.color` | A choice of 'black' or 'white' base color for the heatmap (indicating no instability)
`thr.gain` | A threshold above which will be set as gain
`thr.loss` | A threshold below which will be set as loss
`V.def` | There are 2 different CIN definitions - normalized (value=2) and un-normalized (value=3)
`V.mode` | There are 3 options: 'sum', 'amp' and 'del'

### Value

No value returned. If R_or_C='Regular', it will genearte chromosome level heatmap, If R_or_C='Cytobands',it will generate cytoband level heatmap

### See Also

See accompanying vignette for end-to-end tutorial

### Examples

    ###### Example 1 - Chromosome level

    ## Step 1: Run chromosome CIN
    # This is how command should be run:
    ## Not run:
    run.cin.chr(grl.seg = grl.data)

    ## End(Not run)
    # For this example, we run chr CIN on one threshold only
    data("grl.data")
    run.cin.chr(grl.seg = grl.data, thr.gain=2.25, thr.loss=1.75, V.def=3, V.mode="sum")

    ## Step 2: Plot chromosome level heatmap
    # This is how the command must be called:
    ## Not run:
    comp.heatmap(R_or_C="Regular", clinical.inf=clin.crc, genome.ucsc=hg18.ucsctrack, thr.gain = 2.25,
    thr.loss = 1.75,V.def = 3,V.mode = "sum")

    ## End(Not run)
    # For this example, we run chr heatmap on one threshold only
    comp.heatmap(R_or_C='Regular', clinical.inf=clin.crc, genome.ucsc=hg18.ucsctrack, thr.gain = 2.25,
    thr.loss = 1.75,V.def = 3,V.mode = "sum")

    ###### Example 2 - Cytoband level

    ## Step 1 : Run cytoband CIN
    # This is how command should be run:
    ## Not run:
    run.cin.cyto(grl.seg = grl.data,cnvgr=cnvgr.18.auto, snpgr=snpgr.18.auto,
    genome.ucsc = hg18.ucsctrack)

    ## Step 2: Plot cytoband level heatmap

    comp.heatmap(R_or_C="Cytobands", clinical.inf=clin.crc, genome.ucsc=hg18.ucsctrack,
    thr.gain=2.25, thr.loss=1.75,V.def=3,V.mode="sum")

    ## End(Not run)

[Package CINdex version 1.8.0 Index]